The Kormendy relation of massive elliptical galaxies at z~1.5. Evidence for size evolution ?

We present the morphological analysis based on HST-NIC2 (0.075 arcsec/pixel) images in the F160W filter of a sample of 9 massive field (> 10^{11} M_\odot) galaxies spectroscopically classified as early-types at 1.2<z<1.7. Our analysis shows that all of them are bulge dominated systems. In particular, 6 of them are well fitted by a de Vaucouleurs profile (n=4) suggesting that they can be considered pure elliptical galaxies. The remaining 3 galaxies are better fitted by a Sersic profile with index 1.9<n<2.3 suggesting that a disk-like component could contribute up to 30% to the total light of these galaxies. We derived the effective radius R_e and the mean surface brightness within R_e of our galaxies and we compared them with those of early-types at lower redshifts. We find that the surface brightness of our galaxies should get fainter by 2.5 mag from z~1.5 to z~0 to match the surface brightness of the local ellipticals with comparable R_e, i.e. the local Kormendy relation. Luminosity evolution without morphological changes can only explain half of this effect, as the maximum dimming expected for an elliptical galaxy is ~1.6 mag in this redshift range. Thus, other parameters, possibly structural, may undergo evolution and play an important role in reconciling models and observations. Hypothesizing an evolution of the effective radius of galaxies we find that R_e should increase by a factor 1.5 from z~1.5 to z~0.Comment: Accepted for publication in MNRAS, 15 pages, 8 figure

Photometric redshifts and selection of high redshift galaxies in the NTT and Hubble Deep Fields

We present and compare in this paper new photometric redshift catalogs of the galaxies in three public fields: the NTT Deep Field, the HDF-N and the HDF-S. Photometric redshifts have been obtained for thewhole sample, by adopting a $\chi^2$ minimization technique on a spectral library drawn from the Bruzual and Charlot synthesis models, with the addition of dust and intergalactic absorption. The accuracy, determined from 125 galaxies with known spectroscopic redshifts, is $\sigma_z\sim 0.08 (0.3)$ in the redshift intervals $z=0-1.5 (1.5-3.5)$. The global redshift distribution of I-selected galaxies shows a distinct peak at intermediate redshifts, z~0.6 at I_{AB}<26 and z~0.8 at I_{AB}<27.5 followed by a tail extending to z~6. We also present for the first time the redshift distribution of the total IR-selected sample to faint limits ($Ks \leq 21$ and $J\leq22$). It is found that the number density of galaxies at 1.25<z<1.5 is ~ 0.1 /arcmin^22 at J<=21 and ~1./arcmin^2} at J<22, and drops to 0.3/arcmin^2 (at J<22) at 1.5<z<2. The HDFs data sets are used to compare the different results from color selection criteria and photometric redshifts in detecting galaxies in the redshift range 3.5<z<4.5 Photometric redshifts predict a number of high z candidates in both the HDF-N and HDF-S that is nearly 2 times larger than color selection criteria, and it is shown that this is primarily due to the inclusion of dusty models that were discarded in the original color selection criteria by Madau et al 1998. In several cases, the selection of these objects is made possible by the constraints from the IR bands. Finally, it is shown that galactic M stars may mimic z>5 candidates in the HDF filter set and that the 4 brightest candidates at $z>5$ in the HDF-S are indeed most likely M stars. (ABRIDGED)Comment: Version accepted on July, 20, 2000. To appear on Astronomical Journal, Nov 2000. The data and photometric redshift catalogs presented here are available on line at http://www.mporzio.astro.it/HIGH

Extracting significant signal of news consumption from social networks: the case of Twitter in Italian political elections

According to the Eurobarometer report about EU media use of May 2018, the number of European citizens who consult on-line social networks for accessing information is considerably increasing. In this work we analyse approximately 106 tweets exchanged during the last Italian elections held on March 4, 2018. Using an entropy-based null model discounting the activity of the users, we first identify potential political alliances within the group of verified accounts: if two verified users are retweeted more than expected by the non-verified ones, they are likely to be related. Then, we derive the users’ affiliation to a coalition measuring the polarisation of unverified accounts. Finally, we study the bipartite directed representation of the tweets and retweets network, in which tweets and users are collected on the two layers. Users with the highest out-degree identify the most popular ones, whereas highest out-degree posts are the most “viral”. We identify significant content spreaders with a procedure that allows to statistically validate the connections that cannot be explained by users’ tweeting activity and posts’ virality, using an entropy-based null model as benchmark. The analysis of the directed network of validated retweets reveals signals of the alliances formed after the elections, highlighting commonalities of interests before the event of the national elections